The initial heading of an inertial navigation system (INS) is typically determined with the use of a fine alignment gyrocompassing process or method. An INS alignment is performed either with the IMU at rest on the ground or in motion. A ground or stationary alignment uses gyrocompassing to determine the initial heading or wander angle using the angular rate vector sensed by the IMU from the Earth's rotation rate when the IMU is stationary. The accuracy of a gyrocompassed heading is proportional to the quality of the gyro measurements and the square root of the alignment time.
In general, gyrocompassing requires highly accurate gyroscopes and long alignment times. A ground alignment can also be accomplished with the use of external heading sensors such as magnetic compass or multi-antenna GNSS-based attitude determination system. However, external heading sensors can have disadvantages. A magnetic compass is affected by magnetic disturbance and local magnetic fields and a magnetic compass requires special care in sensor calibration and installation. A multi-antenna GNSS-based attitude determination system is expensive and the GNSS antennas must be separated by as large a distance as possible, which prohibits its use in small vehicle or pedestrian navigation applications.
An in-motion alignment method begins with arbitrarily setting the initial attitude of the IMU to zero degrees roll, pitch and heading, and subsequently uses the AINS Kalman filter to estimate the attitude errors with the aiding from an external velocity and/or position reference source such as a GNSS receiver. The Kalman filter's estimated roll and pitch errors converge quickly regardless of IMU dynamics when position and velocity aiding data are available to the Kalman filter. The Kalman filter's estimated heading error requires a longer time to converge depending on the vehicle dynamics.
For airborne or land vehicle applications, convergence is obtained in about 1 minute if the vehicle executes rapid turns that generate large centripetal accelerations. For man-portable mobile applications, where the dynamics experienced are smaller, in-motion alignment requires a long and possibly unacceptable convergence time.